Francis Teal

In this paper three censuses of manufacturing firms in Ghana for 1962, 1987 and 2003 are used to investigate changes in the firm size distribution and changes in the employment and value-added share across that distribution. It is shown that the censuses for 1987 and 2003 excluded self-employed enterprises with employees which were a rapidly growing part of the industrial structure over the period 1987 to 2003. Using a wider definition of firm, which includes those enterprises, there has been a substantial shift in employment to small firms where productivity is low. Using the wider definition of a firm in 2003 the top 1 per cent of firms produced 63 per cent of value-added. If the narrow definition of firm used in the manufacturing census is applied than the top 1 per cent of firms in 2003 were producing 72 per cent of value-added. These findings are related to the view there is a ‘missing-middle’ in the firm size distribution in Africa.

​Apprenticeships are the most common form of non-academic training in Sub-Saharan Africa where most are provided by the private sector, for a fee, and lead to self-employment rather than to wage jobs. Where the effects have been measured, they show that earnings are not higher, on average, for people who did an apprenticeship than for those who did not. This presents a conundrum. Why would people pay for apprenticeship training that does not benefit them? Research reveals that apprenticeships do benefit some people more than others. Especially striking is that the returns to apprenticeships can fall with the level of education.

​Macro analysis of the sources of income differences has produced very different results as to the importance of education. In this paper we investigate the roles of education and technology in explaining differences in firm level productivity across Ghana and South Korea. The labour productivity differentials across these firms exceed those implied by macro analysis. Median value-added per employee is over thirty times higher in South Korean than in Ghanaian manufacturing firms. We show that if we allow for a non-linear effect of education on output the whole of the average productivity differences across the countries can be explained. We discuss the policy implications that flow from this finding.